Unique continuation for the gradient of eigenfunctions and Wegner estimates for random divergence-type operators

Abstract

We prove a scale-free quantitative unique continuation estimate for the gradient of eigenfunctions of divergence-type operators, i.e. operators of the form $-\mathrm{div}A\nabla$, where the matrix function $A$ is uniformly elliptic. The proof uses a unique continuation principle for elliptic second order operators and a lower bound on the $L^2$-norm of the gradient of eigenfunctions corresponding to strictly positive eigenvalues. As an application, we prove an eigenvalue lifting estimate that allows us to prove a Wegner estimate for random divergence-type operators. Here our approach allows us to get rid of a restrictive covering condition that was essential in previous proofs of Wegner estimates for such models.

24 pages, major revisions

References in corpus (2)

• Band edge localization beyond regular Floquet eigenvalues
• Wegner estimate for random divergence-type operators monotone in the randomness

Cited by in corpus (1)

• Wegner estimate for random divergence-type operators monotone in the randomness